Build a Bioinformatic Analysis Platform and Apply it to Routine Analysis of Microbial Genomics and Comparative Genomics
Protocol for applying Machine Learning models for the transformation of conventional fluorescence images to super-resolution
Human and machine learning pipelines for responsible clinical prediction using high-dimensional data
Mass spectrometry-based proteomic analysis of NSCLC tumor and biopsy samples
Bioinformatics analysis of NSCLC multi-omics data
Deep-insight visible neural network (DI-VNN) for improving interpretability of a non-image deep learning model by data-driven ontology
Resampled dimensional reduction for feature representation in machine learning
Quantifying medical histories with the Kaplan-Meier (KM) estimator for feature extraction of electronic health records in machine learning
Systematic human learning by literature and data mining for feature selection in machine learning
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